This storyboard aims to display the results of an analysis using natural language processing to analyze Amazon electrical product reviews. We’ll be comparing lexical diversity and lexical density of reviews with 1-5 star ratings, investigating the rough importance of words used in reviews of different ratings using TF-IDF analysis, and finish with a rough sentiment analysis using both the AFINN and BING lexicons.
Much of this analysis is shamefully duplicated from this fantasic article I came accross a few years ago by Debbie Liske which aimed to use natural language processing to investigate the lyrics of prince, I’d highly reccommend giving it a read!
This storyboard aims to use natural language processing to analyze Amazon electrical product reviews.
The dataset used in this analysis can be found here. There are tons of different product categories here, so feel free to try this yourself and perhaps compare the features of different types of reviews. If you use the this data for any purpose please cite them!
| overall | word | n | tf | idf | tf_idf |
|---|---|---|---|---|---|
| 1 | product | 7818 | 0.0076728 | 0 | 0 |
| 1 | bought | 7416 | 0.0072782 | 0 | 0 |
| 1 | time | 7196 | 0.0070623 | 0 | 0 |
| 1 | quality | 4686 | 0.0045989 | 0 | 0 |
| 1 | amazon | 4576 | 0.0044910 | 0 | 0 |
| 1 | money | 4443 | 0.0043605 | 0 | 0 |
| 1 | unit | 3817 | 0.0037461 | 0 | 0 |
| 1 | sound | 3508 | 0.0034428 | 0 | 0 |
| 1 | months | 3483 | 0.0034183 | 0 | 0 |
| 1 | return | 3368 | 0.0033054 | 0 | 0 |
| 1 | computer | 3346 | 0.0032838 | 0 | 0 |
| 1 | support | 3265 | 0.0032043 | 0 | 0 |
| 1 | purchased | 3248 | 0.0031877 | 0 | 0 |
| 1 | cable | 3207 | 0.0031474 | 0 | 0 |
| 1 | reviews | 3027 | 0.0029708 | 0 | 0 |
| 1 | fine | 3020 | 0.0029639 | 0 | 0 |
| 1 | price | 2924 | 0.0028697 | 0 | 0 |
| 1 | device | 2905 | 0.0028510 | 0 | 0 |
| 1 | cheap | 2890 | 0.0028363 | 0 | 0 |
| 1 | power | 2776 | 0.0027244 | 0 | 0 |
| overall | word | n | tf | idf | tf_idf |
|---|---|---|---|---|---|
| 5 | price | 57166 | 0.0072611 | 0 | 0 |
| 5 | quality | 51079 | 0.0064879 | 0 | 0 |
| 5 | bought | 47779 | 0.0060688 | 0 | 0 |
| 5 | time | 41376 | 0.0052555 | 0 | 0 |
| 5 | easy | 40266 | 0.0051145 | 0 | 0 |
| 5 | product | 39745 | 0.0050483 | 0 | 0 |
| 5 | sound | 35461 | 0.0045042 | 0 | 0 |
| 5 | cable | 34191 | 0.0043429 | 0 | 0 |
| 5 | camera | 34167 | 0.0043398 | 0 | 0 |
| 5 | recommend | 32428 | 0.0041189 | 0 | 0 |
| 5 | nice | 28656 | 0.0036398 | 0 | 0 |
| 5 | computer | 25743 | 0.0032698 | 0 | 0 |
| 5 | love | 24294 | 0.0030858 | 0 | 0 |
| 5 | perfect | 22454 | 0.0028521 | 0 | 0 |
| 5 | purchased | 21782 | 0.0027667 | 0 | 0 |
| 5 | power | 20941 | 0.0026599 | 0 | 0 |
| 5 | amazon | 20837 | 0.0026467 | 0 | 0 |
| 5 | battery | 20382 | 0.0025889 | 0 | 0 |
| 5 | excellent | 20168 | 0.0025617 | 0 | 0 |
| 5 | fine | 20062 | 0.0025482 | 0 | 0 |